A battery is a device used to store electrical energy. The process of storing electrical energy or power into a battery is referred to as charging the battery. Conversely, the process of removing or using the stored electrical energy from a battery is referred as discharging the battery. The total amount of energy which can be stored in a battery, i.e. a battery's total capacity, depends on the type, size, and age of the battery. The amount of electrical energy stored in a battery is typically referred to as a battery's capacity (Q) and is measured in units of ampere-hours (AH). The unit ampere-hours is indicative of the inverse relationship between a battery's remaining capacity or reserve time and the current being supplied by the battery. Specifically, the greater the current being supplied by the battery, the faster the battery discharges, and thus, the shorter the time the battery can supply such current before completely discharging its stored capacity of electrical energy. Conversely, the smaller the current supplied, the slower the battery discharges, and the longer the battery can supply such current before becoming completely discharged.
The uses of batteries to supply electrical power are as varied as the electrical devices or systems in which they are used. As electrical devices and systems have become increasingly prevalent in consumer and industrial applications, there has been a corresponding increase in the use of batteries. Some electrical systems such as portable electronic devices (i.e., mobile phones, portable computers, radios, hand tools, watches, etc.) use batteries as their primary source of electrical energy. Other electrical systems or devices receive their primary electrical power supply from a power source such as a generator, power plant, or line power supply. Even these devices, however, often utilize batteries as a back-up or secondary supply of electrical power. In such a battery-backed system, if the primary power source fails, the battery can be used to supply electrical power until the primary power supply is reinstated. This scheme of redundant power sources is often utilized in electrical devices or systems in which a temporary loss of power is problematic. Such systems include very complex as well as relatively simple applications. Examples include alarm clocks, where a loss of power could result in the clock losing track of the proper time thus resulting in a false or a late alarm; computers, where an untimely loss of power could result in lost data; and telecommunications systems, where a loss of power could result in a shutdown of communications networks.
Since batteries can only store a limited amount of electrical energy, once that energy has been exhausted the batteries will no longer be able to supply electrical power to the electrical system or device. Obviously, for any electrical device, then, knowing how much battery capacity remains is a convenient feature since a battery's remaining capacity determines the battery's reserve time, i.e., how much longer before the battery supply is exhausted and thus how much longer the electrical device or system may be used. In electrical systems which require an uninterrupted power supply, determining when the battery power supply will be exhausted may not only be a convenient feature, but such capability may be a critical system design feature. In order to ensure an uninterrupted power supply, the remaining battery capacity and reserve time must be accurately predicted such that either the primary power supply can be restored to service, or another alternative power supply can be connected, before the battery power supply is exhausted.
To this end, several methods have been suggested to accurately and reliably predict remaining battery capacity and thus battery reserve time. The initial method used for predicting remaining battery life is strictly empirical, wherein extensive testing of the battery is conducted in order to compile a large database of characteristics indicative of the battery's performance throughout the cycle of the battery from a fully charged state to a fully discharged state. By comparing these predetermined test characteristics to the battery's actual characteristics, as measured during use, one can predict what stage of discharge the batter is in and thus how much battery capacity or reserve time remains.
For this empirical method to yield accurate and reliable results, however, the initial testing has to account for a multitude of factors which could affect the battery's performance. This means the testing must be performed under conditions matching the actual use of the battery as closely as possible. Not only does this mean testing has to be performed for each type and size battery individually, but also the testing should include other external variables such as the load on the battery as well as the battery's temperature and environment (all factors which can affect the battery's performance characteristics). The result is that there are innumerable combinations of such factors which would have to be tested for each battery in order for the empirical data to be useful and accurate for all applications. Moreover, to have test data useful for reliably predicting a specific battery's performance essentially requires duplicating the application in which the battery is going to be used. This is obviously impractical to do for all possible applications. Typically, then, the testing has been standardized by performing the tests with standard loads and standard variables for the surrounding temperature/environment for each of the different types and sizes of batteries. The data from these standardized tests, however, provides limited accuracy and reliability for predicting the remaining battery capacity and reserve time.
In addition to the costly and extensive initial testing required for this empirical method, the apparatus or equipment needed to perform this method can also be costly. Specifically, due to the large database of information required for this method, any computer or other control system using this method would require a large amount of memory to store the relatively large database of predetermined test data used for comparison. The combination of these expenses, as well as the limited usefulness of standardized data with respect to each unique application, and the resulting inaccuracy and unreliability of the predictions based on such standardized data, has made this method largely impractical.
Other more theoretical methods have been suggested to address the inherent limitations of attempting to rely strictly on such empirical methods for predicting the remaining capacity and reserve time of a battery. The fundamental method of prediction, of the prior art, is based on the Peukert equation: EQU t=al.sup.b
where (t) is the reserve time to a given end voltage, (I) is the discharge current and (a) and (b) are empirically determined parameters. The remaining reserve time during discharge is obtained by subtracting the actual time of discharge from the value (t) given by the equation. The only real time data used in this approach is the discharge current (I), while the parameters (a) and (b) must again be experimentally predetermined by extensive testing, data acquisition, and parametric analysis. Since these parameters are empirically derived, the values of these parameters are fixed and do not adapt to changing conditions affecting battery performance such as changing load requirements, temperature, or ageing of the battery.
An attempt to be more responsive to changes in battery behavior during discharge is disclosed in the patent application Ser. No. 08/013272, filed Feb. 4, 1993, submitted by D. Levine et al. which utilizes matrices of predetermined parameters that correlate the slope of the voltage-versus-discharge time at various discharge currents, battery voltages during discharge, and end voltages. The use of voltage-versus-time slopes for prediction allows the method to be highly adaptable to changes in battery behavior during discharge. This method, however, also requires extensive initial testing to derive the data to populate the matrices.
Another approach, disclosed by R. Biagetti and A. Pesco in U.S. Pat. No. 4,952,862, operates by measuring the difference between battery voltage during discharge and the battery plateau voltage, EQU V.sub.battery -V.sub.P.
During discharge this difference is plotted against a ratio of discharged capacity to the total discharge capacity available: EQU Q.sub.removed /Q.sub.to-end-voltage.
This plot, created from measured data, is a single curve having an exponential and a linear region. The curve can then be used to determine remaining capacity and reserve time from the measured discharged capacity (Q.sub.removed) and the plateau voltage (V.sub.p). As in the above described method, extensive prior testing and data analysis of the particular battery being monitored is required, and the method does not account for ageing of the battery since the plateau voltage (V.sub.p) is a predetermined fixed value.
Another approach in determining the reserve time of a discharging battery, disclosed in U.S. Pat. No. 4,876,513, takes advantage of the fact that when battery voltages (corrected for internal resistance) are plotted versus a ratio of ampere-hours remaining to ampere-hours available to a certain discharge voltage, all discharge curves fall on a single curve. The battery voltages are calculated using a battery internal resistance that is measure periodically during discharge.
Although moderately effective, none of these preexisting methods for evaluating the state of a discharging battery works accurately at all temperatures, requires only a minimal number of empirically derived parameters, is independent of the battery size being monitored, and adapts to changing conditions affecting battery performance. In response to these deficiencies, Trung V. Nguyen developed a more accurate apparatus and method of predicting remaining battery capacity (Q) and reserve time (t) of a discharging battery to a selected end voltage. The method is disclosed in U.S. Pat. No. 5,631,540 and is primarily based on measurable battery parameters which do not require extensive pretesting of the battery. The battery reserve time (t) of a discharging battery is determined by an arrangement considering the discharge current (I), battery voltage (V), battery temperature (T), and the battery's internal resistance (R.sub.int). The remaining battery capacity (Q) is determined from the ratio between a maximum theoretical capacity (Q.sub.max) and its present capacity (Q). A term defined by a sum of the battery full charge open circuit voltage (E.sub.oc) and the voltage loss due to the internal resistance of the battery (IR.sub.int) and the battery voltage on discharge (V) divided by the battery temperature (T), is computed as the temperature-corrected battery overvoltage (.eta.): ##EQU1## The characteristics of the battery discharge are reduced to a ratio of the remaining battery capacity to maximum theoretical capacity: ##EQU2## This normalized battery capacity value is plotted versus the temperature-corrected battery overvoltage to produce a discharge characteristic curve that is invariant to discharge rates, temperatures, and battery size. This normalized battery capacity is determined by fitting parameters to the overvoltage value .eta. by the relation: ##EQU3## to characterize the discharge characteristic and determine Q. A reserve time (t) can then be calculated from the determined capacity value (Q) using the relation: ##EQU4## The characteristic curve and the dynamic variables can be stored in a computer and processed continuously to provide a continuing real time prediction of the remaining capacity (Q) and reserve time (t) of the battery on discharge.
Contrary to Mr. Nguyen's belief that this method is dependent only on the battery's internal design, however, the method is not completely invariant to all external factors impacting battery performance, such as ageing, deterioration, and defects in the battery or battery connections. Accordingly, the calculation process disclosed by Nguyen produces results which, although relatively accurate as compared to previous prediction methods, are not always within an acceptable tolerance, especially when the battery exhibits changing performance characteristics over time.
More specifically, in Nguyen's method the internal resistance (R.sub.int) is assigned a constant value equal to the internal resistance of a newly manufactured battery. In application, however, all batteries slowly begin the irreversible ageing process which results in a corresponding decrease in a battery's available capacity. This drop in capacity is partly due to the increase of internal resistance caused by water loss, grid corrosion/deterioration, temperature, or other means. Thus, predictions based on Nguyen's method can lose accuracy a the battery ages.